1 City

2 County

3 Employment Projections

# add geom_hline showing "Total media wages"
# # Change the "horizontal justification" to be left-justified with hjust 

mycols <- c("blue", "red")
ggplot(data=occupation, mapping=aes(x=industry, y=median_wages17, fill=compu)) +
  stat_summary(fun.y=mean, geom="bar") +
  scale_y_continuous(labels=dollar) +
  labs(title="Median Wages by Industry in 2017", x="", y="") + 
  coord_flip() + 
  theme(legend.position="none") + 
  scale_fill_manual(values=mycols) + 
  geom_text(aes(label = median_wages17), color = "black", hjust=-0.1) +
  geom_hline(yintercept = 37690, color="red", size=1, linetype="dashed")

# remove all occupations

occupation <- occupation[2:23,]

occupation$industry <- fct_reorder(occupation$industry, occupation$change2026, mean, na.rm=TRUE)
ggplot(data=occupation, mapping=aes(x=industry, y=change2026, fill=compu)) +
  stat_summary(fun.y=mean, geom="bar") +
  scale_y_continuous() +
  labs(title="Employment Jobs Growth Projection by Industry 2016-2026 ", x="", y="") + 
  coord_flip() + 
  theme(legend.position="none") + 
  scale_fill_manual(values=mycols) + 
  geom_text(aes(label = change2026), color = "black", hjust=-0.1) 

  # geom_hline(yintercept = 37690, color="red", size=1, linetype="dashed")

occupation$industry <- fct_reorder(occupation$industry, occupation$perchange206, mean, na.rm=TRUE)

ggplot(data=occupation, mapping=aes(x=industry, y=perchange206, fill=compu)) +
  stat_summary(fun.y=mean, geom="bar") +
  scale_y_continuous() +
  labs(title="% Employment Growth Projection by Industry 2016-2026 ", x="", y="") + 
  coord_flip() +
  theme(legend.position="none") +
  scale_fill_manual(values=mycols) +
  geom_text(aes(label = perchange206), color = "black", hjust=-0.1)

2017 Employment by major occupational group, 2016 and projected 2026 (Numbers in thousands) [1]. Tech employees are compensated nicely due to this tech boom. For example, in 207 while the annual medialn wage for all occupations was $37,000 in the U.S., it was $84,600 for the computer occupations, second only to $102,000 of the management occupations as shown in Table 1.

4 Dinamic Visualizations

Figure 1 shows the total jobs in the city of Los Angeles and County.

# install imageMagick
# https://www.imagemagick.org/script/download.php#windows

# Tutorials
# https://ryanpeek.github.io/2016-10-19-animated-gif_maps_in_R/
# https://cran.r-project.org/web/packages/magick/vignettes/intro.html

# library(magick) # this is call to animate/read pngs

# save all png files to path folder

# create gif
# list.files(path = "C:/Users/joao_/Downloads/Gif/", pattern = "*.png", full.names = T) %>%
#   map(image_read) %>% # reads each path file
#   image_join() %>% # joins image
#   image_animate(fps=100) %>% # animates, can opt for number of loops
#   image_write("tech_100.gif") # write to current dir

Figure 2 shows the evolution of Tech Jobs by zip code from 2012 to 2017

5 Maps

# Set zero margins in plot window, so that map fits
par(mar=c(0,0,0,0))
# plot(zips.shp, lwd=0.1)

# Plot a specific region - zooms in LA conty
plot(zips.shp, lwd=0.1, xlim=c(-118.510000,-117.820000), ylim=c(33.710000,34.860000))
plot(cadots.rand, add=T, pch=19, cex=0.1, col="#0000ff") # Blue    --- "#09900d" for Green

Fig. X shows dot density for all tech jobs in LA county. Each dot = 10 people

6 Correlation Between the CHCI and the Median House Income of Los Angeles County Zip Codes

Fig. 8 shows the association between the 2012 CHCI and the 2016 median household income of 282 zip codes in L.A. County. We can see a very strong correlation correlation between the human capital level [23] and the household income for the zip code in L.A. It demonstrates the importance to invest in education (chci) in order to create more productive workforce and more high paying jobs.

Source - 5-year American Community Survey 2012-2016 Global Innovation Index 2018, World Bank Population Data 2016, Q11 - Current country of residence [19-21]

7 Conclusions

• Gender imbalance continues (Fig. 1)
• BRICS to outnumber Western countries by 2020 (Fig. 6)
• User prevalence moderatedly-correlated with innovation (Fig. 8)

8 References

1. [1] Assumptions Tech industry employment was calculated using the following: (1) Information jobs (NAICS: 51), and (2) Professional, Scientific, & Technical Skills (NAICS: 54). Data source: Quarterly Census of Employment and Wages (QCEW) developed through a cooperative program between the states and the U.S. Bureau of Labor Statistics.– These data are summarized by Industry Sector (2-digit NAICS).
2. [2] https://www.bls.gov/emp/tables/emp-by-major-occupational-group.htm

Shape Files - https://data.lacity.org/ Los Angeles Open Data ACS

23. [23] http://www.anderson.ucla.edu/centers/ucla-anderson-forecast/projects-and-partnerships/city-human-capital-index

9 Acknowledgements

• This project was largely inspired by conversations with Dr. William Yu, UCLA
• Dynamic Visualizations were inspire by Google Public Data Explorer.
• Fig. 3 and 5 was largely inspired by conversations with Ferran Pujol of McKinsey &Co. Chile.
• Fig. 6 inspired by the charts of @ash316 [15]
• Fig. 1,2,3 inspired by the charts of @paultimothymooney [4]
• Hadley Wickham, for his development of ggplot2 (Fig 7, 8), the open-source statistical analysis & data visualisation based on Leland Wilkinson’s book Grammar of Graphics.

https://flowingdata.com/

https://geocompr.robinlovelace.net/index.html

#googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents

2. [2] https://www.theverge.com/2018/11/2/18057716/google-walkout-20-thousand-employees-ceo-sundar-pichai-meeting
3. [3] https://www.forbes.com/sites/womensmedia/2017/08/03/breaking-down-the-gender-gap-in-data-science/#129d1bb74287
4. [4] https://www.kaggle.com/paultimothymooney/2018-kaggle-machine-learning-data-science-survey
5. [5] https://en.wikipedia.org/wiki/Generations_in_the_workforce
6. [6] Sinton, E (2011). ‘Baby boomers are very privileged human beings’ https://www.telegraph.co.uk/finance/personalfinance/pensions/8840963/Baby-boomers-are-very-privileged-human-beings.html retrieved October 23, 2013 from www.telegraph.co.uk
7. [7] Ken Blanchard Companies. (2009). Next Generation of workers. http://www.kenblanchard.com/img/pub/Blanchard_Next_Generation_of_Workers.pdf Retrieved October 14, 2013, from kenblanchard.com
8. [8] Adecco Group UK and Ireland. (n.d.). Managing the modern workforce. http://www.adeccogroupuk.co.uk/SiteCollectionDocuments/Adecco-Group-Workplace-Revolution.pdf Retrieved October 13, 2013, from www.Adeccouk.co.uk
9. ref. needed
10. [10] https://en.wikipedia.org/wiki/Affluence_in_the_United_States
11. [11] https://www.epi.org/blog/top-1-0-percent-reaches-highest-wages-ever-up-157-percent-since-1979/
12. [12] J. Berengueres, Sketch thinking. 2016
13. [13] https://en.wikipedia.org/wiki/Marimekko#Marimekko_chart
14. [14] ref. needed
15. [15] https://www.kaggle.com/ash316/kaggle-journey-2017-2018
16. [16] https://en.wikipedia.org/wiki/BRICS
17. [17] https://www.kaggle.com/harriken/brics-growth
18. [18] See primary vs. secondary color in https://material.io/design/color/the-color-system.html#color-theme-creation
19. [19] Dutta, S., Reynoso, R.E., Garanasvili, A., Saxena, K., Lanvin, B., Wunsch-Vincent, S., Le?n, L.R. and Guadagno, F., 2018. THE GLOBAL INNOVATION INDEX 2018: ENERGIZING THE WORLD WITH INNOVATION. GLOBAL INNOVATION INDEX 2018, p.1.
20. [20] CSV file global innovation in https://www.globalinnovationindex.org/analysis-indicator
21. [21] World Bank, https://data.worldbank.org/indicator/SP.POP.TOTL
22. [22] https://en.wikipedia.org/wiki/Kendall_rank_correlation_coefficient

The shapefile format is a common way to store data for geographic areas, namely polygons, lines, and points. Each tract is represented as a polygon (i.e. some shape)

Dowload shape files for county from LA Data Portal https://data.lacounty.gov/Geospatial/ZIP-Codes/65v5-jw9f